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Liver fibrosis identification based on ultrasound images captured under varied imaging protocols

CAO Gui-tao 1, SHI Peng-fei 1, HU Bing 2 (1Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, China) (2Department of Ultrasound in Medicine, Shanghai Sixth Hospital, Shanghai Jiao Tong University, Shanghai 200233, China)  
Diagnostic ultrasound is a useful and noninvasive method in clinical medicine. Although due to its qualitative, sub- jective and experience-based nature, ultrasound image interpretation can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features of fractal dimension and the entropies of texture edge co-occurrence matrix based on ultrasound images, which is not sensitive to changes in emission frequency and gain. Then, Fisher linear classifier and support vector machine are employed to test a group of 99 in-vivo liver fibrosis images from 18 patients, as well as other 273 liver images from 18 normal human volunteers.
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